Regional differentiation of human potential indicators

Vyacheslav V. Lokosov, Yelena V. Ryumina, Vladimir V. Ulyanov

Abstract


The purpose of the study presented in this article is an interregional analysis of human potential. The quality of the population proper is investigated at the regional level far less than the quality of the population life. The article provides an extended characteristic of human potential in seven directions: economic activity, demographic processes, physical health, the cultural potential of population, social health, educational potential, the attitude of population to the environment. On the basis of official statistics for 2008–2012, there were selected 63 indicators characterizing human potential in all these directions. In the final result, the correlation analysis has led to the substantiation of the system of indicators for the level of human potential development, consisting of 10 indicators. The system included 3 economic indicators and 7 social indicators characterizing human potential. Upon these indicators the Russian regions were divided in two types of regions by means of hierarchic agglomerative (combining) methods of cluster analysis: the regions with economic indicators and without them. The performed calculations provided the typology of regions by the human potential indicators being stable over time and covering 74.4 % of the Russian population. A substantial interpretation of breaking down regions by groups, identification of both strong and weak aspects of each cluster were made, finding out specific features of the regions falling under the clusters. The obtained results can be used when working out measures for reducing the interregional inequality in the levels of human potential development. To find out what measures can be effective, it is possible to examine the strategic directions of regions’ development in the cluster that is the most successful with respect to the human potential characteristics under investigation.

Keywords


human potential; quality of population; human resources; cluster analysis; regional level; typology of regions; economic indicators; social indicators; Federal subjects; interregional analysis

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References


Ryumia, Ye. V. (2014). Ekologicheskaya kharakteristika kachestva naseleniya [Ecological characteristic of the quality of the population]. Ekonomika regiona [Economy of region], 3, 82–90.

Lokosov, V. V. (Ed.). (2015). Narodonaselenie sovremennoy Rossii. Vosproizvodstvo i razvitie [Population of modern Russia. Reproduction and development]. Moscow: Ekon-Inform Publ., 411.

Sorokin, P. (1922). Sovremennoye sostoyanie Rossii [Current state of Russia]. Prague: Khutor Publ., 112.

Soboleva, I. V. (2007). Chelovecheskiy potentsial rossiyskoy ekonomiki: problemy sokhraneniya i razvitiya [Human potential of the Russian economy: problems of preservation and development]. Moscow: Nauka Publ., 202.

Frolov, I. E. (Ed.). (1999). Chelovecheskiy potentsial: opyt kompleksnogo podkhoda [Human potential: experience of an integrated approach]. Moscow: Editorial URSS Publ., 176.

Chelovecheskoye razvitie. Novoye izmerenie sotsialno-ekonomicheskogo progressa [Human development. New measurement of social and economic progress]. Moscow: Prava cheloveka Publ., 636.

Bobylev, S. N. (Ed.) (2013). Doklad o chelovecheskom razvitii v Rossiyskoy Federatsii 2013 «Ustoychivoye razvitie: vyzovy Rio» [Report on human development in the Russian Federation 2013 "A sustainable development: challenges of Rio"]. Moscow: RA ILF Publ., 202.

Grigoryev, L. M. & Bobylev, S. N. (2014). Doklad o chelovecheskom razvitii v Rossiyskoy Federatsii za 2014 god [The report on human development in the Russian Federation for 2014]. Moscow: Analiticheskiy tsentr pri Pravitelstve Rossiyskoy Federatsii Publ., 204.

Human Development Report 2013. The Rise of the South: Human Progress in a Diverse World. (2014). New York: UNDP, 216.

Human Development Report 2014: Sustaining Human Progress. Reducing Vulnerabilities and Building Resilience. (2014). New York: UNDP, 239.

Toksanbaeva, M. S. (2006). Sotsialnyye interesy rabotnikov i ispolyzovanie trudovogo potentsiala [Social interests of workers and use of labor potential]. Moscow: Nauka Publ., 259.

Ayvazyan, S. A., Bukhshtaber, V. M., Yenyukov, I. S. & Meshalkin, L. D. (1989). Prikladnaya statistika. Klassifikatsiya i snizhenie razmernosti [Applied statistics. Classification and decrease in dimension]. Moscow: Finansy i statistika Publ., 607.

Everitt, B. S., Landau, S., Leese, M. & Stahl, D. (2011). Cluster analysis. Fifth Edition. U.K: John Wiley & Sons, 346.

Rokach, L. A (2010). Survey of Clustering Algorithms. Data Mining and Knowledge Discovery Handbook. Second Edition. In: Oded Maimon and Lior Rokach (Eds). New York: Springer, 269–298.

Dan, A. Simovici & Chabane Djeraba (2014). Mathematical Tools for Data Mining. Second edition. London: Springer-Verlag, 831.




DOI: https://doi.org/10.15826/recon.2016.2.1.003

Copyright (c) 2018 Vyacheslav V. Lokosov, Yelena V. Ryumina, Vladimir V. Ulyanov

Сertificate of registration media Эл № ФС77-80764 от 23.04.2021
Online ISSN 2412-0731